Robot Learning Engineer - Manipulation

Highlights

• Build manipulation policies from task definition to reliable real-robot deployment.
• Train and evaluate policies on real robots doing real industrial tasks.
• Turn failures into better data, models, and evaluation task after task.

What they offer

• Equity

Ideal candidate

A hands-on roboticist energized by real hardware who takes manipulation from demo to dependable deployment and measures success by reliable performance on customer lines.

Requirements

• 1+ years of professional experience
• Bachelor's degree in Computer Science, Software Engineering, or equivalent
• Trained or fine-tuned a learned manipulation policy and deployed and evaluated it on a physical robot
• Strong Python and PyTorch skills with ability to write maintainable training, evaluation, and deployment code
• Practical depth in imitation learning and at least one modern policy family such as vision-language-action models, diffusion policies, or action-chunking transformers